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, you will leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modeling systems as graphs and encoding nonlinearities in these. As
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Supervisory Team: Prof Middleton, Prof Altamirano PhD Supervisor: Matt Middleton Project description: Black holes grow by accreting material through a disc which is bright across the EM spectrum
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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position is available at the Department of Pharmacy , Faculty of Health Sciences , within the Microbial Pharmacology and Population Biology (MicroPop) research group , led by Prof. Pål J. Johnsen
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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features allow overcoming such limitation? The PhD project will be largely experimental with some modelling aspects, and will begin with an identification of a set of research questions based on a detailed
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diseases, and how these influence, or are influenced by, labor force participation and income. In addition, you will develop simulation models to predict how different policies could reduce the disease
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Supervisory Team: Dr N.C. Townsend, Prof A. Murphy PhD Supervisor: Nick Townsend Project description: In this PhD project you will explore novel wave energy harvesting systems for maritime robotic
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, analysis, and model choice while retaining strong error guarantees. This means that researchers can adapt their research questions and sampling plans to the data as they come in and in a way that is as model
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to train an AI model that predicts the cis-regulatory code for synthetic genomes (i.e. for cell-free gene expression systems) and correlates the experimental conditions within the synthetic cell